PT  - JOURNAL ARTICLE
AU  - Ethan B. Trepka
AU  - Shude Zhu
AU  - Ruobing Xia
AU  - Xiaomo Chen
AU  - Tirin Moore
TI  - Functional Connections Among Neurons within Single Columns of Macaque V1
AID  - 10.1101/2022.02.18.481095
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.02.18.481095
4099  - http://biorxiv.org/content/early/2022/02/21/2022.02.18.481095.short
4100  - http://biorxiv.org/content/early/2022/02/21/2022.02.18.481095.full
AB  - Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional connections between neurons thereby providing an unprecedented view of local circuit interactions. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally connected neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the strength and synchrony of functional connections across the cortical column. Despite neurons residing within the same column, both measures of functional connectivity depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of connected pairs to categorize functional connections between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional connections within the full population. These classes of functional connections were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.Competing Interest StatementThe authors have declared no competing interest.